Chavda Vivek P, Valu Disha D, Parikh Palak K, Tiwari Nikita, Chhipa Abu Sufiyan, Shukla Somanshi, Patel Snehal S, Balar Pankti C, Paiva-Santos Ana Cláudia, Patravale Vandana
Department of Pharmaceutics and Pharmaceutical Technology, L. M. College of Pharmacy, Ahmedabad 380009, Gujarat, India.
Formulation and Drug Product Development, Biopharma Division, Intas Pharmaceutical Ltd., 3000-548 Moraiya, Ahmedabad 380054, Gujarat, India.
Vaccines (Basel). 2023 Feb 6;11(2):374. doi: 10.3390/vaccines11020374.
Accurate identification at an early stage of infection is critical for effective care of any infectious disease. The "coronavirus disease 2019 (COVID-19)" outbreak, caused by the virus "Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)", corresponds to the current and global pandemic, characterized by several developing variants, many of which are classified as variants of concern (VOCs) by the "World Health Organization (WHO, Geneva, Switzerland)". The primary diagnosis of infection is made using either the molecular technique of RT-PCR, which detects parts of the viral genome's RNA, or immunodiagnostic procedures, which identify viral proteins or antibodies generated by the host. As the demand for the RT-PCR test grew fast, several inexperienced producers joined the market with innovative kits, and an increasing number of laboratories joined the diagnostic field, rendering the test results increasingly prone to mistakes. It is difficult to determine how the outcomes of one unnoticed result could influence decisions about patient quarantine and social isolation, particularly when the patients themselves are health care providers. The development of point-of-care testing helps in the rapid in-field diagnosis of the disease, and such testing can also be used as a bedside monitor for mapping the progression of the disease in critical patients. In this review, we have provided the readers with available molecular diagnostic techniques and their pitfalls in detecting emerging VOCs of SARS-CoV-2, and lastly, we have discussed AI-ML- and nanotechnology-based smart diagnostic techniques for SARS-CoV-2 detection.
在感染的早期阶段进行准确识别对于有效治疗任何传染病至关重要。由“严重急性呼吸综合征冠状病毒2（SARS-CoV-2）”病毒引起的“2019冠状病毒病（COVID-19）”疫情，是当前的全球大流行，其特点是出现了多种变异毒株，其中许多被世界卫生组织（瑞士日内瓦，WHO）列为值得关注的变异株（VOCs）。感染的初步诊断可使用检测病毒基因组RNA部分的RT-PCR分子技术，或识别病毒蛋白或宿主产生的抗体的免疫诊断程序。随着对RT-PCR检测的需求迅速增长，一些缺乏经验的生产商带着创新试剂盒进入市场，越来越多的实验室进入诊断领域，导致检测结果越来越容易出错。很难确定一个未被注意到的结果会如何影响患者隔离和社会隔离的决策，尤其是当患者本身是医护人员时。即时检测的发展有助于在现场快速诊断疾病，这种检测还可以用作床边监测器，以描绘重症患者疾病的进展情况。在这篇综述中，我们向读者介绍了现有的分子诊断技术及其在检测SARS-CoV-2新兴VOCs方面的缺陷，最后，我们讨论了基于人工智能-机器学习和纳米技术的SARS-CoV-2智能诊断技术。
